def test_opennmt_tf_variables_conversion(tmpdir):
import opennmt
model_path = os.path.join(
_TEST_DATA_DIR,
"models",
"transliteration-aren-all",
"opennmt_tf",
"v2",
"checkpoint",
)
src_vocab = opennmt.data.Vocab.from_file(
os.path.join(model_path, "ar.vocab"))
tgt_vocab = opennmt.data.Vocab.from_file(
os.path.join(model_path, "en.vocab"))
_, variables = opennmt_tf.load_model(model_path)
converter = ctranslate2.converters.OpenNMTTFConverter(
ctranslate2.specs.TransformerSpec(6, 8),
src_vocab,
tgt_vocab,
variables=variables,
)
output_dir = str(tmpdir.join("ctranslate2_model"))
converter.convert(output_dir)
translator = ctranslate2.Translator(output_dir)
output = translator.translate_batch([["آ", "ت", "ز", "م", "و", "ن"]])
assert output[0].hypotheses[0] == ["a", "t", "z", "m", "o", "n"]
def test_opennmt_tf_variables_conversion(tmpdir):
model_path = os.path.join(
_TEST_DATA_DIR, "models", "transliteration-aren-all", "opennmt_tf", "v2", "checkpoint")
_, variables, src_vocab, tgt_vocab = opennmt_tf.load_model(
model_path,
src_vocab=os.path.join(model_path, "ar.vocab"),
tgt_vocab=os.path.join(model_path, "en.vocab"))
converter = ctranslate2.converters.OpenNMTTFConverter(
src_vocab=src_vocab, tgt_vocab=tgt_vocab, variables=variables)
output_dir = str(tmpdir.join("ctranslate2_model"))
converter.convert(output_dir, ctranslate2.specs.TransformerBase())
translator = ctranslate2.Translator(output_dir)
output = translator.translate_batch([["آ" ,"ت" ,"ز" ,"م" ,"و" ,"ن"]])
assert output[0][0]["tokens"] == ["a", "t", "z", "m", "o", "n"]